{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:05:25Z","timestamp":1777611925514,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19030000"],"award-info":[{"award-number":["XDA19030000"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19090000"],"award-info":[{"award-number":["XDA19090000"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19090121"],"award-info":[{"award-number":["XDA19090121"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2022YFS0486"],"award-info":[{"award-number":["2022YFS0486"]}]},{"name":"the Key Research and Development Program of the Sichuan Provincial Science and Technology Department","award":["XDA19030000"],"award-info":[{"award-number":["XDA19030000"]}]},{"name":"the Key Research and Development Program of the Sichuan Provincial Science and Technology Department","award":["XDA19090000"],"award-info":[{"award-number":["XDA19090000"]}]},{"name":"the Key Research and Development Program of the Sichuan Provincial Science and Technology Department","award":["XDA19090121"],"award-info":[{"award-number":["XDA19090121"]}]},{"name":"the Key Research and Development Program of the Sichuan Provincial Science and Technology Department","award":["2022YFS0486"],"award-info":[{"award-number":["2022YFS0486"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Long-term degradation of black soil has led to reductions in soil fertility and ecological service functions, which have seriously threatened national food security and regional ecological security. This study is motivated by the UN\u2019s Sustainable Development Goal (SDG) 2\u2014Zero Hunger, specifically, SDG 2.4 Sustainable Food Production Systems. The aim was to monitor the soil organic matter (SOM) content of black soil and its dynamics via hyperspectral remote sensing inversion. This is of great significance to the effective utilization and sustainable development of black soil resources. Taking the typical black soil area of Northeast China as an example, the hyperspectral data of ground features were compared with SOM contents measured in soil samples to correlate SOM with spectral features. Based on their quantitative relationship, a dynamic fitness inertia weighted particle swarm optimization (DPSO) algorithm is proposed, which balances the global and local search abilities of a particle swarm optimization algorithm. The DPSO algorithm is applied to the parameter adjustment of an artificial neural network (BPNN), which is used instead of a traditional error back propagation algorithm, to build a DPSO-BPNN model. Then a global optimal analytical expression of hyperspectral inversion is obtained to improve the generalization ability and stability of the remote sensing quantitative inversion model. The results show that DPSO-BPNN model is more stable and accurate than existing models, such as multiple stepwise regression, partial least squares, and BP neural network models (adjust complex coefficient of determination = 0.89, root mean square error = 1.58, relative recent deviation = 2.93). The results of DPSO-BPNN inversion are basically consistent with the trend in SOM contents measured during surface geochemical exploration. As such, this study provides a basis for hyperspectral remote sensing inversion and monitoring of the SOM contents in black soil.<\/jats:p>","DOI":"10.3390\/rs14174316","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:19:01Z","timestamp":1662077941000},"page":"4316","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Hyperspectral Remote Sensing Inversion and Monitoring of Organic Matter in Black Soil Based on Dynamic Fitness Inertia Weight Particle Swarm Optimization Neural Network"],"prefix":"10.3390","volume":"14","author":[{"given":"Ruichun","family":"Chang","sequence":"first","affiliation":[{"name":"College of Mathematics and Physics, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Digital Hu Line Research Institute, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7579-1968","authenticated-orcid":false,"given":"Zhe","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mathematics and Physics, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Digital Hu Line Research Institute, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China"},{"name":"International Research Centre of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daming","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin Center of Geological Survey, China Geological Survey, Tianjin 300170, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Mathematics and Physics, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Digital Hu Line Research Institute, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","first-page":"127","article-title":"Soil organic matter content inversion model with remote sensing image in field scale of blacksoil area","volume":"34","author":"Liu","year":"2018","journal-title":"Trans. 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